Using word embeddings to investigate cultural biases. [PDF]
Br J Soc Psychol, 2023 Durrheim K +3 more
europepmc +2 more sources
Relational Word Embeddings [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 While word embeddings have been shown to implicitly encode various forms of attributional knowledge, the extent to which they capture relational information is far more limited. In previous work, this limitation has been addressed by incorporating relational knowledge from external knowledge bases when learning the word embedding.
Camacho Collados, Jose +2 more
openaire +3 more sources
Historical representations of social groups across 200 years of word embeddings from Google Books. [PDF]
Proc Natl Acad Sci U S A, 2022 Charlesworth TES, Caliskan A, Banaji MR.
europepmc +2 more sources
Improving Word Embedding Using Variational Dropout
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings.
Zainab Albujasim +3 more
doaj +1 more source
Neuro-Symbolic Word Embedding Using Textual and Knowledge Graph Information
Applied Sciences, 2022 The construction of high-quality word embeddings is essential in natural language processing. In existing approaches using a large text corpus, the word embeddings learn only sequential patterns in the context; thus, accurate learning of the syntax and ...
Dongsuk Oh, Jungwoo Lim, Heuiseok Lim
doaj +1 more source
Learned Text Representation for Amharic Information Retrieval and Natural Language Processing
Information, 2023 Over the past few years, word embeddings and bidirectional encoder representations from transformers (BERT) models have brought better solutions to learning text representations for natural language processing (NLP) and other tasks. Many NLP applications
Tilahun Yeshambel +2 more
doaj +1 more source
Improved biomedical word embeddings in the transformer era. [PDF]
J Biomed Inform, 2021 Noh J, Kavuluru R.
europepmc +2 more sources
Refined Global Word Embeddings Based on Sentiment Concept for Sentiment Analysis
IEEE Access, 2021 Sentiment Analysis is an important research direction of natural language processing, and it is widely used in politics, news and other fields. Word embeddings play a significant role in sentiment analysis.
Yabing Wang +5 more
doaj +1 more source
Natural language understanding of map navigation queries in Roman Urdu by joint entity and intent determination [PDF]
PeerJ Computer Science, 2021 Navigation based task-oriented dialogue systems provide users with a natural way of communicating with maps and navigation software. Natural language understanding (NLU) is the first step for a task-oriented dialogue system.
Javeria Hassan +2 more
doaj +2 more sources
Slovene and Croatian word embeddings in terms of gender occupational analogies
Slovenščina 2.0: Empirične, aplikativne in interdisciplinarne raziskave, 2021 In recent years, the use of deep neural networks and dense vector embeddings for text representation have led to excellent results in the field of computational understanding of natural language.
Matej Ulčar +3 more
doaj +1 more source